What problem does it solve? Content teams running high-volume AI-assisted production pipelines lack visibility into whether quality scores are improving, which pipeline phases are slowest, and which brands or content types underperform. This Skill aggregates historical tracking records into an ASCII dashboard with trends, outlier detection, and alerts. ## Core Features & Use Cases - Quality Trend Analysis: Computes mean, median, percentiles, and regression-based trend direction for composite and per-dimension quality scores over 7/30/90-day windows. - Pipeline Timing Breakdown: Compares per-phase processing times against configured benchmarks to identify bottlenecks and throughput metrics. - Compliance & Citation Monitoring: Tracks citation density, brand compliance scores, feedback loop frequency, and hallucination catch rates. - Alert Rules: Flags quality declines, phase slowdowns, citation drops, and loop spikes based on thresholds in config/analytics-config.json. - Use Case: A content lead runs the dashboard monthly to discover that whitepaper validation is running 1.9x over benchmark and one brand's scores declined for three consecutive pieces, prompting a brand profile review. ## Quick Start Ask the assistant to show the ContentForge analytics dashboard for the last 30 days across all brands.
